Welcome to my Distill course page. Here you can find all course logistics and content.
This is the course website for DATA-101 Introductory Data Analysis.
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Lecture: Wednesdays, 13:00-14:30
Labs: Fridays, biweekly, 13:00-14:30
The textbook below (Wickham and Grolemund 2017) is not required but will be referred to throughout the course. It is available online and for free. A hardcopy of the text is on reserve at the university library.
When there are assigned articles or readings, these will be posted 2-3 days before the corresponding lecture under the Lectures tab of this course website.
This course is assigned 3 credit hours1.
We’d like to thank the following funding sources for making this work possible: Source 1, Source 2, and Source 3.
Wasai. n.d. “Lorem Ipsum.” https://loremipsum.io/.
Wickham, Hadley, and Garrett Grolemund. 2017. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. 1st ed. O’Reilly Media, Inc. https://r4ds.had.co.nz/.
A footnote goes here!↩
Text and figures are licensed under Creative Commons Attribution CC BY 4.0. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".